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1,891 results for “Field data”
Picturing global substorm dynamics in the magnetotail using low-altitude ELFIN measurements and data mining-based magnetic field reconstructions (SST19 Reconstruction Output Dataset for Review)
<p>The dataset containing SST19 reconstruction output data accompanying the GRL submission for "Picturing global substorm dynamics in the magnetotail using low-altitude ELFIN measurements and data mining-based magnetic field reconstructions"</p>
Data in the paper Accuracy Evaluation of River Surface Flow Field Measurement Methods based on Satellite Video
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Supporting data files for simulations in "Wind fields in Category 1-3 tropical cyclones are not fully represented in wind turbine design standards"
<p>This deposit contains the time-series output from the WRF-LES simulations of three tropical cyclones used in "Wind fields in Category 1-3 tropical cyclones are not fully represented in wind turbine design standards".</p>
MAPS 21A–D in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
MAPS 21A–D. Geographic range maps for Philippine records of (A) Lycodon alcalai; (B) Lycodon bibonius; (C) Lycodon capucinus; (D) Lycodon chrysoprateros.
MAPS 28A–D in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
MAPS 28A–D. Geographic range maps for Philippine records of (A) Oligodon modestus; (B) Oligodon notospilus; (C) Oligodon perkinsi; (D) Ophiophagus hannah.
Data for "Spatial scales of rising-tone chorus in a dipole magnetic field: two-dimensional particle-in-cell simulation"
<p>The GCPIC simulation output data and the corresponding data analysis code.</p>
Raw data for: Okada et al., Photopharmacological modulation of hippocampal local field potential by caged-glutamate with MicroLED probe
<p>Matlab data of LFPs (sampling rate, 1k/sec; microV)</p>
Data for "Entangling gates on degenerate spin qubits dressed by a global field"
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Model input data, simulation output data and processed data presented in "Modelling the three-dimensional, diagnostic anisotropy field of an ice rise"
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Fig. 10 in Introgression at the emerging secondary contact zone of magpie Pica pica subspecies (Aves: Corvidae): integrating data on nuclear and mitochondrial markers, vocalizations, and field observations
Fig. 10 Spectrograms of chatter calls of pure P. p. leucoptera, pure P. p. jankowskii, and hybrids. a leucoptera, pair #4, Choibalsan, eastern Mongolia. b jankowskii, pair #6, Vladivostok, Russian Far East. c, d Bilingual hybrid, the same bird from the pair #24, Kerulen, eastern Mongolia. e Hybrid with mixed call, pair #39, Kerulen. f Presumably hybrid with mixed call, pair #5, Kerulen. X-axis—time in s; Y-axis—frequency in kHz
Fig. 8 in Introgression at the emerging secondary contact zone of magpie Pica pica subspecies (Aves: Corvidae): integrating data on nuclear and mitochondrial markers, vocalizations, and field observations
Fig. 8 Genetic structure of the contact zone and its vicinities by mtDNA and SNPs. Above—distribution of haplotypes of mitochondrial CR along conditional population numbers I–VI depicted in Fig. 3. Green—western haplotype; red—eastern haplotype. Below— graphical representation of individual contributions from nuclear
Fig. 3 in Introgression at the emerging secondary contact zone of magpie Pica pica subspecies (Aves: Corvidae): integrating data on nuclear and mitochondrial markers, vocalizations, and field observations
Fig. 3 Map of sampling localities for nuclear SNP analysis. Distribution of genotypes of nuclear SNPs revealed by ddRAD analysis are shown with blue circles for Pica pica leucoptera and red circles for Pica pica jankowskii. Bi-colored circles mean mixed (hybrid) genotype: portion of blue/red corresponds to probability of it belonging to one of the groups, as revealed in the Structure analysis. Numbers
Fig. 1 in Introgression at the emerging secondary contact zone of magpie Pica pica subspecies (Aves: Corvidae): integrating data on nuclear and mitochondrial markers, vocalizations, and field observations
Fig. 1 Map of Pica pica s.l. subspecies. The study area in the contact zone is indicated by a rectangle. Question marks indicate regions of unclear subspecies distribution. The white star indicates the terra typica for Pica pica anderssoni in eastern China
Raw Data for Publication "Using Supervised Learning to Classify Metadata of Research Data by Field of Study"
<p>Automated classification of metadata of research data by their field of study can be used in scientometric research, by repository service providers, and in the context of research data aggregation services. To evaluate different machine learning approaches, data from the DataCite index have been downloaded in May 2019 with a GeRDI harvester (filtering out any metadata without a qualified subject, i.e. a subject with either a subjectName or a subjectURI) . These is the resulting raw data set.</p>
Data for: Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction (Part 4/5)
<p>This data set consists of MRI measurement data for liver scans acquired with a 3D stack-of-stars multi-echo FLASH sequence during free breathing as described in:</p> <p>Zhengguo Tan, Christina Unterberg-Buchwald, Moritz Blumenthal, Nick Scholand, Philip Schaten, Christian Holme, Xiaoqing Wang, Dirk Raddatz, Martin Uecker. <a href="https://doi.org/10.1109/TMI.2022.3228075">Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction.</a> IEEE Transactions on Medical Imaging 42:1374-1387 (2023) </p> <p>The data stored in the format of the BART toolbox (DOI: 10.5281/zenodo.592960).</p>
Data for: Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction (Part 5/5)
<p>This data set consists of MRI measurement data for liver scans acquired with a 3D stack-of-stars multi-echo FLASH sequence during free breathing as described in:</p> <p>Zhengguo Tan, Christina Unterberg-Buchwald, Moritz Blumenthal, Nick Scholand, Philip Schaten, Christian Holme, Xiaoqing Wang, Dirk Raddatz, Martin Uecker. <a href="https://doi.org/10.1109/TMI.2022.3228075">Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction.</a> IEEE Transactions on Medical Imaging 42:1374-1387 (2023) </p> <p>The data stored in the format of the BART toolbox (DOI: 10.5281/zenodo.592960).</p>
Data for: Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction (Part 3/5)
<p>This data set consists of MRI measurement data for liver scans acquired with a 3D stack-of-stars multi-echo FLASH sequence during free breathing as described in:</p> <p>Zhengguo Tan, Christina Unterberg-Buchwald, Moritz Blumenthal, Nick Scholand, Philip Schaten, Christian Holme, Xiaoqing Wang, Dirk Raddatz, Martin Uecker. <a href="https://doi.org/10.1109/TMI.2022.3228075">Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction.</a> IEEE Transactions on Medical Imaging 42:1374-1387 (2023) </p> <p>The data stored in the format of the BART toolbox (DOI: 10.5281/zenodo.592960).</p>
Data for: Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction (Part 1/5)
<p>This data set consists of MRI measurement data for liver scans acquired with a 3D stack-of-stars multi-echo FLASH sequence during free breathing as described in:</p> <p>Zhengguo Tan, Christina Unterberg-Buchwald, Moritz Blumenthal, Nick Scholand, Philip Schaten, Christian Holme, Xiaoqing Wang, Dirk Raddatz, Martin Uecker. <a href="https://doi.org/10.1109/TMI.2022.3228075">Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction.</a> IEEE Transactions on Medical Imaging 42:1374-1387 (2023) </p> <p>The data stored in the format of the BART toolbox (DOI: 10.5281/zenodo.592960).</p>
Data for: Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction (Part 2/5)
<p>This data set consists of MRI measurement data for liver scans acquired with a 3D stack-of-stars multi-echo FLASH sequence during free breathing as described in:</p> <p>Zhengguo Tan, Christina Unterberg-Buchwald, Moritz Blumenthal, Nick Scholand, Philip Schaten, Christian Holme, Xiaoqing Wang, Dirk Raddatz, Martin Uecker. <a href="https://doi.org/10.1109/TMI.2022.3228075">Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction.</a> IEEE Transactions on Medical Imaging 42:1374-1387 (2023) </p> <p>The data stored in the format of the BART toolbox (DOI: 10.5281/zenodo.592960).</p>
Field data for article "Root rot increases the vulnerability of Norway spruce trees to Ips typographus infestation"
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.